LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
Qwen2.5 Bakeneko 32B Instruct GPTQ int8 (rinna/qwen2.5-bakeneko-32b-instruct-gptq-int8)
QwQ Bakeneko 32B AWQ (rinna/qwq-bakeneko-32b-awq)
Qwen2.5 Bakeneko 32B Instruct GPTQ int4 (rinna/qwen2.5-bakeneko-32b-instruct-gptq-int4)
Qwen2.5 Bakeneko 32B Instruct V2 GPTQ int8 (rinna/qwen2.5-bakeneko-32b-instruct-v2-gptq-int8)
Hugging Face GitHub Launch Blog Documentation Technical Report License : Apache 2.0 Authors : Google DeepMind
Description: Gemma 4 31B IT is an open multimodal model built by Google DeepMind that handles text and image inputs, can process video as sequences of frames, and generates text output. It is designed to deliver frontier-level performance for reasoning, agentic workflows, coding,…
Hugging Face GitHub Launch Blog Documentation Technical Report License : Apache 2.0 Authors : Google DeepMind
Hugging Face GitHub Launch Blog Documentation Technical Report License : Apache 2.0 Authors : Google DeepMind
Hugging Face GitHub Launch Blog Documentation Technical Report License : Apache 2.0 Authors : Google DeepMind
Description: Gemma 4 26B IT is an open multimodal model built by Google DeepMind that handles text and image inputs, can process video as sequences of frames, and generates text output. It is designed to deliver frontier-level performance for reasoning, agentic workflows, coding,…
:--- :--- Total Parameters 120B (12B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 1× B200 OR 1× DGX Spark Supported Languages English, French, German, Italian, Japanese,…
:--- :--- Total Parameters 120B (12B active) Architecture LatentMoE - Mamba-2 + MoE + Attention hybrid with Multi-Token Prediction (MTP) Context Length Up to 1M tokens Minimum GPU Requirement 8× H100-80GB Supported Languages English, French, German, Italian, Japanese, Spanish, Ch…